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On-line Recognition of Critical Driving Situations

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F21%3A00351008" target="_blank" >RIV/68407700:21260/21:00351008 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.14311/NNW.2021.31.012" target="_blank" >https://doi.org/10.14311/NNW.2021.31.012</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.14311/NNW.2021.31.012" target="_blank" >10.14311/NNW.2021.31.012</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    On-line Recognition of Critical Driving Situations

  • Original language description

    According to the statistics about vehicle accidents, there are many causes such as traffic violations, reduced concentration, micro sleep, hasty aggression, but the most frequent cause of accidents at highways is a carelessness of the driver and violation of keeping a safe distance. Producers of vehicles try to take into account this situation by development of assistance systems which are able to avoid accidents or at least to mitigate its consequences. This urgent situation leaded to the described project of investigation of behavior of drivers in dangerous situations occurring in vehicle driving. The research is to help in solution of the present unsatisfactory situation in driving accidents. The developed decisionmaking algorithm of detection serious driving situations that can lead to accidents was tested in the laboratory of driving simulators in FTS CTU, Prague. The data for its testing resembled highway traffic.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10103 - Statistics and probability

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Neural Network World

  • ISSN

    1210-0552

  • e-ISSN

    2336-4335

  • Volume of the periodical

    31

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    CZ - CZECH REPUBLIC

  • Number of pages

    12

  • Pages from-to

    227-238

  • UT code for WoS article

    000691212500004

  • EID of the result in the Scopus database

    2-s2.0-85115446725